This research aimed to enhance the antibacterial activity of silver nanoparticles (AgNPs) synthesized from silver nitrate (AgNO3) using aloe vera extract. It was performed by means of incorporating AgNPs on an activated carbon nanoparticle (ACNPs) under ultrasonic agitation (40 kHz, 2 × 50 watt) for 30 min in an aqueous colloidal medium. The successful AgNPs synthesis was clarified with both Ultraviolet-Visible (UV-Vis) and Fourier Transform Infrared (FTIR) spectrophotometers. The successful AgNPs-ACNPs incorporation and its particle size analysis was performed using Transmission Electron Microscope (TEM). The brown color suspension generation and UV-Vis's spectra maximum wavelength at around 480 nm confirmed the existence of AgNPs. The particle sizes of the produced AgNPs were about 5 to 10 nm in the majority number, which collectively surrounded the aloe vera extract secondary metabolites formed core-shell like nanostructure of 8.20 ± 2.05 nm in average size, while ACNPs themselves were about 20.10 ± 1.52 nm in average size formed particles cluster, and 48.00 ± 8.37 nm in average size as stacking of other particles. The antibacterial activity of the synthesized AgNPs and AgNPs-immobilized ACNPs was 57.58% and 63.64%, respectively (for E. coli); 61.25%, and 93.49%, respectively (for S. aureus). In addition, when the AgNPs-immobilized ACNPs material was coated on the cotton and polyester fabrics, the antibacterial activity of the materials changed, becoming 19.23% (cotton; E. coli), 31.73% (polyester; E. coli), 13.36% (cotton; S. aureus), 21.15% (polyester; S. aureus).
The aim of this study was to evaluate the point doses using a distribution of the size-specific dose estimate (SSDE) from axial CT images of in-house phantoms having diameters from 8 to 40 cm. In-house phantoms made of polyester-resin (PESR) mixed with methyl ethyl ketone peroxide (MEKP) were used. The phantoms were built with different diameter sizes of 8, 16, 24, 32, and 40 cm. The phantoms were scanned by Siemens a SOMATOM Perspective-128 slice CT scanner with constant input parameters. The point doses were interpolated from the central SSDE (SSDEc) and the peripheral SSDE (SSDEp). The SSDEc and SSDEp were calculated from the SSDE with h- and k-factors. The point doses were compared to the direct measurements using the nanoDot™ optically-stimulated luminescence dosimeter (OSLD) in dedicated holes on the phantoms. It was found that the point dose decreases as the phantom diameter increased. The doses obtained using two approaches differed by 11% on average. The highest difference was 40% and the lowest difference was
Objective. To develop an algorithm to measure slice thickness running on three types of Catphan phantoms with the ability to adapt to any misalignment and rotation of the phantoms.Method. Images of Catphan 500, 504, and 604 phantoms were examined. In addition, images with various slice thicknesses ranging from 1.5 to 10.0 mm, distance to the iso-center and phantom rotations were also examined. The automatic slice thickness algorithm was carried out by processing only objects within a circle having a diameter of half the diameter of the phantom. A segmentation was performed within an inner circle with dynamic thresholds to produce binary images with wire and bead objects within it. Region properties were used to distinguish wire ramps and bead objects. At each identified wire ramp, the angle was detected using the Hough transform. Profile lines were then placed on each ramp based on the centroid coordinates and detected angles, and the full-width at half maximum (FWHM) was determined for the average profile. The slice thickness was obtained by multiplying the FWHM by the tangent of the ramp angle (23°).Results. Automatic measurements work well and have only a small difference (<0.5 mm) from manual measurements. For slice thickness variation, automatic measurement successfully performs segmentation and correctly locates the profile line on all wire ramps. The results show measured slice thicknesses that are close (<3 mm) to the nominal thickness at thin slices, but slightly deviated for thicker slices. There is a strong correlation (R2= 0.873) between automatic and manual measurements. Testing the algorithm at various distances from the iso-center and phantom rotation angle also produced accurate results.Conclusion. An automated algorithm for measuring slice thickness on three types of Catphan CT phantom images has been developed. The algorithm works well on various thicknesses, distances from the iso-center, and phantom rotations.